Recently, significant research has been done in Super-Resolution (SR) methods for
augmenting the spatial resolution of the Magnetic Resonance (MR) images, which aids the …

High resolution (HR) Magnetic Resonance Imaging (MRI) is a popular diagnostic tool, which
provides detail structural information and rich textures, benefiting accurate diagnosis and …

Alzheimer's disease (AD) is a neurodegenerative brain disorder that leads to a steady
decline in brain function and the death of brain cells. AD condition causes dementia, which …

Surface-based analysis of magnetic resonance imaging (MRI) data of the brain plays an
important role in clinical and research applications. To achieve accurate three-dimensional …

Deep Learning (DL)-based segmentation methods have been quite successful in various
medical imaging applications. The main bottleneck of these methods is the scarcity of quality …

Pediatric medical imaging represents a real challenge for physicians, as children who are
patients often move during the examination, and it causes the appearance of different …

Improving the image resolution and acquisition speed of magnetic resonance imaging (MRI)
is a challenging problem. There are mainly two strategies dealing with the speed-resolution …

Abstract Diffusion Weighted Imaging (DWI) is one of the standard MRI images that are used
for the diagnosis of brain tumors. However, the acquired DW images suffer from artifacts …

While generative adversarial networks (GAN) have been widely applied in various settings,
the competitive deep learning frameworks such as GANs were not as popular in medical …

Magnetic resonance imaging (MRI) is a non-invasive imaging technique that can produce
high spatial resolution 3D images, especially for non-bony parts or soft tissues. Higher …